Journal Information
Computational Intelligence and Neuroscience (CIN)
Impact Factor:

Call For Papers
Computational Intelligence and Neuroscience is a forum for the interdisciplinary field of neural computing, neural engineering and artificial intelligence, where neuroscientists, cognitive scientists, engineers, psychologists, physicists, computer scientists, and artificial intelligence investigators among others can publish their work in one periodical that bridges the gap between neuroscience, artificial intelligence and engineering.

The journal provides research and review papers at an interdisciplinary level, with the field of intelligent systems for computational neuroscience as its focus. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. All items relevant to building theoretical and practical systems are within its scope, including contributions in the area of applicable neural networks theory, supervised and unsupervised learning methods, algorithms, architectures, performance measures, applied statistics, software simulations, hardware implementations, benchmarks, system engineering and integration and innovative applications.

The journal spans the disciplines of computer science, mathematics, physics, psychology, cognitive science, medicine and neurobiology amongst others. Work on computational intelligence and neuroscience refers to work on theoretical and computational aspects of the development and functioning of the nervous system, which can be at the level of networks of neurons or at the cellular or the sub-cellular level.

Topics of the journal include but are not limited to computational, theoretical, experimental, clinical and applied aspects of the following:

    Neural modeling and neural-computation
    Neural signal processing
    Brain-computer interfacing
    Neurofeedback, neural rehabilitation
    Brain waves, neuroimaging (fMRI, EEG, MEG, PET, NIR)
    Neural circuits: artificial and biological
    Neural control and neural system analysis
    Learning theory (supervised/unsupervised/reinforcement learning)
    Knowledge based neural networks, probabilistic, spatial, and temporal knowledge representation and reasoning
    Learning Classifiers
    Fusion of neural network- fuzzy systems- evolutionary algorithms
    Biologically inspired Intelligent agents (architectures, environments, adaptation/ learning and knowledge management)
    Bayesian networks and probabilistic reasoning
    Swarm intelligence, Ant colony optimization, Multi-agent systems
    Computational aspects of perceptual systems; Perception of different (visual, auditory and tactile) modalities; Perception and selective attention
    Long-term, Short-term, and Working memory
    Multi-level (neural, psychological, computational) analysis of cognitive phenomena
    Integrated theories of natural and artificial cognitive systems
    Information-theoretic, control-theoretic, and decision-theoretic approaches to neuroscience
    Multi-disciplinary computational approaches to the study of creativity, learning, knowledge and inference, emotion and motivation, awareness and consciousness, perception and action, decision making and action, etc.
    Cognitive systems from artificial life, dynamical systems, complex systems perspectives
    Neurobiologically inspired evolutionary systems

Featured contributions will fall into original research papers or review articles. Articles are expected to be high quality contributions representing new and significant research, developments or applications of practical use and value. Decisions will be made based on originality, technical soundness, clarity of exposition, scientific contribution and multidisciplinary impact of the article.
Last updated by Dou Sun in 2017-04-30
Special Issues
Special Issue on Neurocomputing Methods for Innovative Multimedia Systems
Submission Date: 2017-07-28

The production and usage of multimedia content have grown significantly in the last few years owing to many factors including increased processing power, faster networks, cheaper storage devices, and growing popularity of social media websites. This rapid generation of multimedia content demands efficient techniques for multimedia computing, communication, storage, content analysis, understanding, retrieval, annotation, tagging, and other innovative applications. Developments in neurocomputing provide promising opportunities for multimedia processing. Recently, neurocomputing methods have been employed by researchers on various aspects of multimedia systems including context based retrieval, multimedia understanding, object detection and recognition, and multimedia surveillance. The purpose of this special issue is to explore the possibilities of applying the following aspects (not limited to the given topics) of computational intelligence and neurocomputing to multimedia processing: neural networks, deep learning, biologically inspired learning systems, biological neural network modeling, computational learning theory, and novel neurocomputing methods. The special issue seeks original contributions on usage of the above-mentioned technologies of computational intelligence and neurocomputing for all domains of multimedia processing. Potential topics include but are not limited to the following: Multimedia storage Content based multimedia retrieval Multimedia tagging and archiving Multimedia communications Multimedia security and watermarking Multimedia information encoding and decoding Multimedia data analysis for surveillance and compound security Multimedia applications Multimedia content analysis and understanding Multimedia and data fusion in personal, sensor, p2p, and ad hoc networks Mobile multimedia processing Multimedia knowledge extraction and reasoning Multimedia recommender systems Interactive multimedia applications Multimedia language description Multimedia refereeing expression Authors can submit their manuscripts through the Manuscript Tracking System at Manuscript Due Friday, 28 July 2017 First Round of Reviews Friday, 20 October 2017 Publication Date Friday, 15 December 2017
Last updated by Dou Sun in 2017-04-30
Special Issue on Advances in Human-Computer Interactions: Methods, Algorithms, and Applications
Submission Date: 2017-08-11

The recent widespread of new technologies and devices for the fruition of multimedia contents (e.g., head-mounted-displays, augmented reality devices, smartphones, and tablets) has been changing the modality of accessing and exploring the digital information, by introducing novel human-computer interaction (HCI) modalities. The even growing market demand, on the one hand, has pushed the diffusion of such technologies; on the other hand, it has hampered a detailed analysis of their effects on the users. In particular, perceptual evidence from cognitive sciences and neurosciences has to be considered during the design of HCI systems in order to decrease visual fatigue and cybersickness and to lead to natural HCI in virtual and augmented reality (VR/AR) environments. Moreover, computer science and artificial intelligence can provide techniques to design systems that adapt themselves to the specific characteristics of each user by producing personalized interfaces that allow a natural HCI, by taking into account the sensorimotor control aspects that arise by using such systems. The aim of this special issue is to call for high-quality research articles as well as review articles with a focus on perceptual aspects and computational intelligence techniques to improve the HCI systems in order to obtain natural and ecological ways to interact with digital contents in VR and AR environments, but not only. Potential topics include but are not limited to the following: Natural and ecological HCI in virtual/augmented/mixed reality environments Computational intelligence approach to improve users’ experience Sensorimotor control in virtual/augmented/mixed reality environments and in HCI systems Cognitive science and psychological research on human perception and effects of HCI interfaces Hand/face/body tracking and activity recognition Vision neuroscience and computational vision models for HCI Haptic-based and human-robot interfaces in virtual/augmented/mixed reality environments Misperception issues and undesired effects in visualization devices (e.g., S3D displays and head-mounted displays) Passive BCI-based HCI and eye-tracking for HCI Applications based on S3D displays, smartphones, tablets, and head-mounted displays Authors can submit their manuscripts through the Manuscript Tracking System at Manuscript Due Friday, 11 August 2017 First Round of Reviews Friday, 3 November 2017 Publication Date Friday, 29 December 2017
Last updated by Dou Sun in 2017-04-30
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